GInPipe

GInPipe estimates SARS-CoV-2 infection incidence from viral genome sequences to reconstruct temporal transmission dynamics and account for biases introduced by variable testing policies.

Key Features:

• Genome-Based Estimation: Uses SARS-CoV-2 genomic data to estimate infection incidence independently of reported case counts.
• Bias Mitigation: Mitigates biases introduced by varying national testing policies that affect detection and reporting of cases.
• Phylodynamic Independence: Reconstructs pandemic waves without requiring complex phylodynamic reconstructions.
• Rapid Execution: Executes within minutes on very large datasets, enabling near real-time analysis.

Scientific Applications:

• Incidence Reconstruction: Reconstructs incidence histories from viral sequences for regions such as Denmark, Scotland, Switzerland, and Victoria (Australia).
• Policy Evaluation: Assesses how different testing policies influence the probability of diagnosing and reporting infections and identified periods of significant under-reporting in mid-2020 across several countries.
• Pandemic Monitoring: Provides a genome-based perspective to complement surveillance tools and inform public-health understanding of SARS-CoV-2 spread.

Methodology:

Validated against simulated outbreak data and compared with more complex phylodynamic analyses to ensure accurate reconstruction of incidence dynamics from viral sequence data alone.